1. Field of the Invention
The present invention relates to an evaluating device suitable for a case where PRML (Partial Response Maximum Likelihood) decoding processing is performed on a reproduced signal from a recording medium, for example, a reproducing apparatus that includes such an evaluating device and reproduces information recorded on a recording medium, and an evaluating method.
2. Description of the Related Art
For example, as a method for evaluating signal quality of a reproduced signal from an optical disk, a method of evaluating time interval jitter (TI jitter) is known. TI jitter refers to variations (jitter) in time difference (time interval) between timing of a binary-level analog signal obtained by inputting a reproduced signal and a bit determination level to a comparator and timing of an edge of a clock synchronously reproduced from the reproduced signal.
Such a method of evaluating signal quality using TI jitter has been used as an evaluation method correlated to a bit error rate because in bit detection using an analog binary signal, variations in timing of edges of the binary signal directly affect the bit error rate. For CDs (Compact Discs), DVDs (Digital Versatile Discs) and the like using such analog binary detection, in particular, the method of evaluating signal quality using TI jitter has been widely used as a very effective signal evaluation method.
On the other hand, it has been confirmed that the above-described bit detection using an analog binary signal cannot secure a sufficiently low bit error rate as the density of information recorded on optical disks has been increased. For a Blu-Ray Disc or the like as a higher-density optical disk, in particular, a method referred to as PRML (Partial Response Maximum Likelihood) detection is now common as a bit detection method.
PRML is a technology that combines a process of partial response and a technology of maximum likelihood detection. Partial response refers to a process of returning an output longer than one bit in response to a one-bit input, that is, a process of making a determination by a plurality of input bits of the output. In particular, a process of obtaining a reproduced signal as a signal obtained by multiplying an input of four consecutive information bits by 1, 2, 2, and 1 in this order and adding the results, as often used for optical disks such as the Blu-Ray Disc and the like, is expressed as PR(1, 2, 2, 1).
Maximum likelihood detection is a method of defining a distance referred to as a path metric between two signal strings, determining a distance between an actual signal and a signal predicted from an assumed bit sequence, and detecting a bit sequence providing the closest distance. Incidentally, the path metric is defined as a distance obtained by adding the squares of differences in amplitude between two signals at same times over a whole time. Viterbi detection is used to search for the bit sequence providing the closest distance.
Partial response maximum likelihood combining these methods is a method of adjusting a signal obtained from bit information on a recording medium such that the signal is in a partial response process by a filter referred to as an equalizer, determining a path metric between the resulting reproduced signal and the partial response of an assumed bit sequence, and detecting a bit sequence providing the closest distance.
An algorithm based on the above-mentioned Viterbi detection is effective in actually searching for a bit sequence providing a minimum path metric.
For the Viterbi detection, a Viterbi detector including a plurality of states formed with consecutive bits of a predetermined length as a unit and branches represented by transitions between the states is used, and is configured to detect a desired bit sequence efficiently from among all possible bit sequences.
An actual circuit is provided with two registers, that is, a register referred to as a path metric register for each state, for storing a path metric between a partial response sequence and a signal up to the state, and a register referred to as a path memory register, for storing a flow of a bit sequence (path memory) up to the state. The circuit is also provided with an operation unit referred to as a branch metric unit for each branch, for calculating a path metric between a partial response sequence and a signal at the bit.
The Viterbi detector can bring various bit sequences into one-to-one correspondence with individual paths passing through the above-described states. A path metric between a partial response sequence passing through these paths and an actual signal (reproduced signal) is obtained by sequentially adding together the above-mentioned branch metrics of inter-state transitions forming the paths, that is, branches.
Further, a path that minimizes the above-described path metric can be selected by comparing the magnitudes of path metrics of two branches or less reached in each state, and sequentially selecting a path with a smaller path metric. Information on this selection is transferred to the path memory register, whereby information representing a path reaching each state by a bit sequence is stored. The value of the path memory register ultimately converges to a bit sequence that minimizes the path metric while being updated sequentially, and the result is output.
Thus, it is possible to search efficiently for a bit sequence that produces a partial response sequence closest to the reproduced signal as described above from a viewpoint of the path metric.
The bit detection using PRML is not directly affected by TI jitter as fluctuation in the direction of a time axis. That is, TI jitter does not necessarily have a correlation with a bit error rate in the bit detection using PRML, and thus is not necessarily appropriate as an index of signal quality.
In the case of PRML, fluctuation in the direction of an amplitude axis has a direct relation to the bit error rate in the bit detection. Hence, for the bit detection using PRML, an index incorporating fluctuation in the direction of an amplitude axis is desirable as a conventional index corresponding to the bit error rate.
As described above, the method of bit detection by PRML is an algorithm that compares the magnitudes of a path metric between a partial response sequence obtained from a correct bit sequence and a reproduced signal and a path metric between a partial response sequence obtained from an erroneous bit sequence and the reproduced signal, retains a closer path, that is, a path with a smaller path metric as a more likely path, and sets a path ultimately surviving after repetition of this operation (maximum likelihood path) as a result of detection.
According to such an algorithm, a large difference between the path metrics of the two closest paths (suppose that the two closest paths are a maximum likelihood path Pa and a second path Pb) with smallest path metric values as candidates selected for the ultimately surviving path indicates that the surviving path is more likely, whereas a small difference between the path metrics of the two closest paths indicates that the surviving path is more unlikely, that is, there is a stronger possibility of an detection error (see FIGS. 16A and 16B).
In other words, correct bit detection is performed when the path metric for the maximum likelihood path is smaller than the path metric for the second path. On the other hand, an error occurs when the path metric for the maximum likelihood path is larger than the path metric for the second path.
Thus, the capability of the PRML bit detection and consequently the signal quality of the reproduced signal can be determined on the basis of difference between the former path metric and the latter path metric.
That is, the difference between the path metric for the maximum likelihood path and the path metric for the second path is effectively used as an index corresponding to the bit error rate in PRML. Specifically, statistical information based on for example a variance value of such a metric difference is used.
When the PRML method is employed, difference patterns (error patterns) between the maximum likelihood path and the second path when detection errors actually occur are limited to a certain extent. Examples thereof include a one-bit error caused by an edge shifted by an amount corresponding to one bit, for example, and a two-bit error caused by disappearance of a 2T mark as a shortest mark, for example.
Error patterns actually appearing as an error in an early stage of use of PRML decoding for disk reproduction were limited substantially 100% to one error pattern. It was therefore possible to evaluate signal quality properly by obtaining a variance value of metric differences as described above only for the only error pattern.
However, with a recent further increase in recording density of the disk, error patterns that appear as an actual error have not been limited to the single pattern, and a plurality of patterns have come to contribute to errors.
Thus, when a variance value is obtained only for the single error pattern as in the conventional case, the contributions of other error patterns are not considered, and therefore a proper signal quality index may not be obtained.
Incidentally, even when a plurality of error patterns thus contribute to errors, in a case where the contribution of one error pattern (for example one-bit error) is prominently large, for example, a variance value of metric differences obtained for this error pattern can be treated as a signal evaluation index reflecting a total (overall) error occurrence rate.
For example, Japanese Patent Laid-open No. 2003-141823 describes a technique that sets a variance value of metric differences obtained for an error pattern having a minimum Euclidean distance as a total signal evaluation index.
However, when the contribution of one error pattern to errors is not dominant and rates of contribution of respective error patterns to a total error rate are comparable to each other, a proper signal quality evaluating index cannot be obtained unless the total error rate is estimated in consideration of the rates of contribution of the respective error patterns to the total error rate.
Accordingly, when the rates of contribution of the respective error patterns to the total error rate are thus comparable to each other, estimating the total error rate by obtaining a variance value of metric differences for each error pattern and assigning a weight to these variance values according to the respective contribution rates is considered.
Under an assumption that a distribution of metric differences for a certain error pattern k can be approximated by a normal distribution (Gaussian distribution), letting dk2 be a Euclidean distance between a maximum likelihood path and a second path in the case of the error pattern k, relation between a variance value of the metric differences for the error pattern k and a bit error rate bERk can be expressed by an integral of an exponential function referred to as an error function such as the following Equation 1.
                              bER          k                =                                                            A                k                                                              2                  ⁢                                      πσ                    k                    2                                                                        ⁢                                          ∫                                  x                  <                  0                                            ⁢                                                exp                  (                                      -                                                                                            (                                                      x                            -                                                          d                              k                              2                                                                                )                                                2                                                                    2                        ⁢                                                  σ                          k                          2                                                                                                      }                                ⁢                                  ⅆ                  x                                                              =                                                    A                k                            2                        ⁢                          {                              erfc                ⁡                                  (                                                            d                      k                      2                                                                                      2                        ⁢                                                  σ                          k                          2                                                                                                      )                                            }                                                          [                  Equation          ⁢                                          ⁢          1                ]            where Ak denotes a rate of contribution of the variance value of the metric differences for the error pattern k to a total error rate.
Hence, according to Equation 1, the bit error rate bERk can be obtained for each error pattern such that the rate of contribution of each error pattern is factored in. The total error rate can be estimated by adding together the values of such bit error rates.